This research had a cross-sectional design, involving students from the Esporte Cidadão (Citizen Sports) Project of the Sports Secretariat of the city of Indaiatuba (SP, Brazil). The entire data collection process, as well as the handling of personal data of the adolescents, followed the principles of compliance with the Lei Geral de Proteção de Dados Pessoais (General Data Protection Law), preserving and strictly regulating the manipulation of personal data through consensual consent (Botelho, 2020).

The operationalization was carried out through the invitation and acceptance by parents/legal guardians, who received clarification about the research and signed the Informed Consent Form, ensuring the reliability and confidentiality of the collected information. Subsequently, the parent/guardian completed the socioeconomic and demographic questionnaire. After obtaining their consent, the assessment of quality of life was conducted with the adolescents. The study complied with ethical requirements and was submitted and approved by the Ethics Committee of the Faculty of Pharmaceutical Sciences at the University of São Paulo, Opinion No. 792945.

At the beginning of the data collection cycle, the original version of the instrument consisted of 51 items distributed across eight domains. After obtaining the first version, the instrument was administered to 1,289 adolescents, with 7.03% being male and 32.97% female. In terms of age, around 70% of the participants were aged 14 or younger, while the remaining were older.

Regarding socioeconomic questions, the monthly family income was obtained using income brackets based on values divided in terms of minimum wage3, where it was found that 37.30% of the families had a monthly income of up to two minimum wages, while 5.77% had an income above eight minimum wages. Based on the Economic Classification of Brazil, used by the Instituto Brasileiro de Geografia e Estatística (IBGE, Brazilian Institute of Geography and Statistics), in this study, 50.19% of the surveyed families were classified as economically belonging to the Brazilian Class C, while 44.40% were classified as Class B. In terms of the education level of the parents/legal guardians, 22% did not complete elementary school, 45.65% completed high school, and 11.54% had a college degree (IBGE, 2015; Oka, 2016).

Analyzing the responses in descriptive terms for each dimension, the group recorded an mean score of 2.05 points for the overall scale. The most affected dimensions were: Eating Habits (mean score of 1.65), Stress Control (mean score of 1.81), Physical Activity (mean score of 1.81), Sleep and Rest (mean score of 2.08), Leisure and Entertainment (mean score of 2.17), and Preventive Behavior (mean score of 2.17). The dimensions with the highest mean scores were Personal Well-being (mean score of 2.42) and Social Relationships (mean score of 2.26).

In the assessment of the coefficient of variation of the responses, it was observed that the distribution of items was not homogeneous, as the coefficient of variation exceeded 25%, indicating that the results presented a high variability (Rizzo, n.d.). Since it is a scale from 0 to 3, the values were not highly concentrated in one particular value. The most important aspect for the study is the correlation between these items.

Moving on to inferential analyses, the correlations ranged from 0.075 (item 3.3) to 0.474 (item 4.1). When analyzing the Cronbach’s alpha achieved in each of the dimensions, satisfactory values were obtained (all domains had values above 0.50), and they were similar to the Total Alpha of the scale (0.833), indicating good internal consistency of the instrument (Pasquali, 2010), as shown in Table 1.

In addition to assessing internal consistency, the investigation of instrument reliability, using the split-half coefficient, also yielded satisfactory results, with a significant association between the scores of the first and second halves. The Spearman-Brown coefficient had a value of 0.612, and the Guttman split-half coefficient was 0.604, both with an “ideal parameter ≥ 0.50,” (Rossetti, 2018, p. 40), as recommended by Martins (2006). Thus, it can be said that the instrument demonstrates both reliability and validity, also supported by the Split-Half Technique.

Regarding the instrument’s construct validity analysis, it is worth highlighting, in Table 2, the Explained Total Variance Factorial Analysis, which identified the 15 factors selected through variable correlation. When observing the Initial Eigenvalue column in the Eigenvalue item, values above 1.000 are selected, resulting in the first 15 components meeting this criterion.

Considering the Rotated Component Matrix analysis (Table 3), a procedure was developed to determine the questions that define the domains by selecting components with factor loadings above 0.50, suggesting they are unidimensional as they measure the same factor. Thus, following McDonald and Ho’s (2002) approach, the questions associated with each domain were identified, and in some cases, components ranging from 0.30 to 0.50 and the maximum values that each question obtained were considered as strength to be included in a factor. Some questions did not reach a value above 0.500, for example, question 3 of dimension 2 (maximum = 0.307). Consequently, the questions strongly associated with each dimension were identified, prioritizing the initial factors that provide the highest correlation explanation.

Analyzing the grouping of their respective factor loadings, the dimensions were defined based on the most explanatory questions. Thus, the final selection of questions within the dimensions was obtained from a statistical perspective. It is important to note that seven (7) factors did not specifically align with any dimension and were therefore not included in the final instrument. However, it is worth highlighting that items 2.3, 6.1, and 6.3, despite having low factor loadings (below 0.50), were retained in the final version of the instrument due to their strong Cronbach’s alpha in their respective dimensions. On the other hand, items 3.10, 6.5, 8.5, and 8.7 no longer strongly align with any specific factor. Thus, the analysis that determined the factor loadings criteria was decided in conjunction with Cronbach’s alpha.

Considering the analysis of the final instrument in conjunction with the results of the Factorial Analysis, the Cronbach’s alpha values were recalculated, taking into account some exclusion indications. The results indicate that the dimensions had alpha values above 0.6, and the Cronbach’s alpha value for the total scale remained high (0.833), demonstrating good reliability and validity of the final instrument.

The proposal for the development/creation of the new instrument undergoes a new configuration, achieving good fit. The analyses indicated that some variables should be excluded or improved. At this point, it was necessary to discuss whether removing an item would contribute to an increase in the Cronbach’s alpha coefficient of its respective factor or if this increase would not justify its removal, considering that all factors exhibit satisfactory internal consistency values (Hongyu et al., 2016; Manly & Alberto, 2019).

The instrument that emerged at the end of this study consisted of eight domains with a total of 33 items (Table 4). Eighteen items were excluded, following the rigor of the methodology chosen to validate the Instrumento de Avaliação da Qualidade de Vida de Adolescentes (Instrument for Assessing the Quality of Life of Adolescents) (Constantino, 2018). However, it is important to highlight the need to test the instrument on other groups of adolescents with diverse socioeconomic and demographic backgrounds in order to identify potential new indicators of their quality of life.

The present study focuses on the validation of an instrument that assesses the lifestyle of adolescents and, therefore, was not designed to assess hypotheses or compare subpopulations. Thus, it does not involve comparisons between different population groups. In the current research, care was taken to identify adolescents’ behaviors and orientations based on their own patterns, with the aim of providing information and stimuli for qualitative changes in these behaviors and habits (Scheer et al., 2019).

Benincasa et al. (2015) emphasize the importance of analyzing programs that investigate the population’s lifestyle as a significant means for future preventive policies. In this direction, Buss et al. (2020) consider and expand on this concept by stating that the health-disease process and its determinants have a connection between scientific and popular knowledge, driven by public and private investments and the population’s commitment to quality of life.

In terms of sociodemographic factors, in terms of gender, there was a heterogeneous distribution that does not follow the population trend of adolescents in Brazil – which, according to data from IBGE (2015), represents 18% of the total population, with 50.40% male and 49.60% female. This result is likely due to the choices of sports modalities included in the study, which predominantly appeal to a male audience.

Regarding socioeconomic data, a differentiated profile of the researched population was identified for income- and education-related questions. Referring to the question of the legal guardian’s educational level, the mean number of years of study for the age group of 25 years and older reflects the educational status of a society. Basic education in Brazil consists of three cycles (called Ensino Fundamental I and II, and Ensino Médio) – in the USA (Elementary, Middle, and High School) – corresponding to 12 years of study. The IBGE (2015) shows that the mean number of years of study in the country was 7.7 years, indicating that most people did not complete Middle School. In this sense, it can be stated that the sample has a significantly higher mean number of years of study.

About monthly family income, it was found that the population in this study has a standard well above the national scenario as shown in IBGE data (2015), which reported the mean nominal per capita household income in Brazil as BRL 1,052.00 and BRL 1,432.00 in the state of São Paulo, considered the largest industrial hub in the country. This perspective highlights that the families who participated in this study have a high level of education as well as a good classification of family income. However, this poses a limitation, suggesting that further studies should include individuals from different socioeconomic backgrounds. Additionally, due to the study’s focus on a specific population, the results are exclusive to this community and cannot be generalized.

Regarding psychometric aspects, Echevarría-Guanilo et al. (2019) recommend the importance of using instruments that assess the population following a rigorous methodology, considering the key psychometric properties, with reliability and validity analysis being relevant in this context. It is also necessary to obtain an assessment regarding the instrument in question, allowing for the identification of whether it measures what it intends to measure, and particularly, when adapted, whether it will continue to measure the same construct.

In the present study, when considering the items used to construct the constructs, separated by domain, the related values were generally high. However, Bettine et al. (2019) emphasize that many students are still not interested in the medium and long-term effects that a satisfactory lifestyle can bring. Supporting this understanding, the findings of Strelhow et al. (2010) indicate that the analysis of the lifestyle of adolescents/students is not considered positive.

Examining the correlations presented among all the items, it was observed that they do not show a consistent pattern in the collected responses. Souza et al. (2017) suggest that high correlations indicate a similar response pattern between constructs, characterizing inconsistency in the instrument. They also recommend the elimination of items with correlations above 0.8 and alpha below 0.30.

The psychometric characteristics of the instrument met the criteria related to reliability and validity analysis, demonstrating good internal consistency of the domains measured by Cronbach’s alpha coefficient and the Spearman-Brown and Guttman split-half coefficients, as outlined by Pasquali (2016) and Rosetti (2018). In line with this, Hutz et al. (2015) also corroborate, when considering reliability as a psychometric property that represents the stability of the items comprising the instrument, enabling its replicability and understanding its capacity to differentiate the various levels of performance it aims to assess.

Regarding the analysis of instrument validity, Souza et al. (2017) argue that it cannot be established in a single study but rather through multiple investigations of the theory being measured. They also emphasize the need to thoroughly understand the instrument - its items, domains, assessment methods, and especially measurement properties – before using it.

Echevarría-Guanilo et al. (2019) outline that construct validity refers to the degree to which an instrument is measuring the construct of interest, examining the theoretical relationship between the instrument’s items and the concepts contained in the theory, thereby providing evidence for the interpretation of the proposed values.

Based on the results of this validation study, the instrument demonstrated adequate psychometric properties and can be useful in identifying the impact of different changes to the lifestyle of adolescents and assisting in the choice of public health policies (Buss et al., 2020). However, caution should be exercised regarding the results, as the selected sample is limited to urban, metropolitan adolescents involved in a sports project within the school system, representing the specific focus of this research.

In this sense, further investigations will be necessary to understand different social spectrums in terms of health-promoting or risky lifestyles as well as additional analyses of validity and reliability, including examinations of Item Response Theory. However, the analysis conducted here yielded satisfactory indices, demonstrating that the instrument developed to investigate the lifestyle of adolescents through a biopsychosocial perspective showed adequate internal consistency and can be considered validated.

Considering the findings and limitations of the present study, it is suggested that new validity research be conducted with a stratified sample to assess the instrument’s performance in different economic and sociocultural contexts, contributing to its stability. Such approaches will allow for a more consistent assessment of the retention or removal of items for use in the Brazilian reality, as demonstrated in studies of validated instruments archived in the Rimas repository (http://rimas.uc.pt/).

Thus, as emphasized by Camaliont and Boccalandro (2017), reflecting on adolescent health means considering the various ways of experiencing adolescence and life, making efforts to build interdisciplinary practices with the aim of providing more comprehensive, concrete, and historically constructed assistance, articulating the various dimensions within the biological, psychological, and social realms.

The instrument analyzed in this paper possesses adequate psychometric properties, demonstrating satisfactory characteristics of internal consistency, validity, and reliability. However, this research represents an initial investigation and is far from answering the numerous questions related to the application of an instrument to assess the quality of life of adolescents in the Brazilian context. Regional cultural variables, sociocultural differences, and peculiarities of specific situations deserve in-depth study to enable the instrument to achieve the breadth it aims for. Nevertheless, the methodology employed in its development indicates that it plays an important role in studying the quality of life of adolescents in Brazil, while also allowing for comparisons with data from other population groups.